code: def __init__(
      self,
      rank: int,
      world_size: int,
      backend: str = "gloo",
      local_size: Optional[int] = None,
  ) -> None:
      self.rank = rank
      self.world_size = world_size
      self.backend = backend
      self.local_size = local_size
  
      if backend == "nccl":
          device = torch.device(f"cuda:{rank}")
          torch.cuda.set_device(device)
      else:
          device = torch.device("cpu")
      self.device: torch.device = device
      torch.use_deterministic_algorithms(True)
      if torch.cuda.is_available():
          torch.backends.cudnn.allow_tf32 = False
          torch.backends.cuda.matmul.allow_tf32 = False
      self.pg: Optional[dist.ProcessGroup] = None
  
file_path: torchrec/torchrec/distributed/test_utils/multi_process.py
imports: import multiprocessing
  import os
  import unittest
  from typing import Any, Callable, Dict, List, Optional
  import torch
  import torch.distributed
  from torchrec.distributed.comm import _CROSS_PG, _INTRA_PG
  from torchrec.test_utils import get_free_port, init_distributed_single_host, seed_and_log
label_desc: Use image node_id 1 to create a new MultiProcessContext object  with example: obj = MultiProcessContext(rank, world_size, backend, local_size)